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Polyhydroxyalkanoate (PHA)-producing bacteria represent a powerful synthetic biology chassis for waste bioconversion and bio-upcycling where PHAs can be produced as the final products. In this study, we present a seamless plasmid construction for orthogonal expression of recombinant PET hydrolase (PETase) in model PHA-producing bacteria P. putida and C. necator. To this end, this study described seamless cloning and expression methods utilizing SureVector (SV) system for generating pSV-Ortho-PHA (pSVOP) expression platform in bioengineered P. putida and C. necator. Genetic parts specifically Trc promoter, pBBR1 origin of replication, anchoring proteins and signal sequences were utilized for the transformation of pSVOP-based plasmid in electrocompetent cells and orthogonal expression of PETase in both P. putida and C. necator. Validation steps in confirming functional expression of PETase activity in corresponding PETase-expressing strains were also described to demonstrate seamless and detailed methods in establishing bioengineered P. putida and C. necator as whole-cell biocatalysts tailored for plastic bio-upcycling.â¢Seamless plasmid construction for orthogonal expression in PHA-producing bacteria.â¢Step-by-step guide for high-efficiency generation of electrotransformants of P. putida and C. necator.â¢Adaptable methods for rapid strain development (Design, Build, Test and Learn) for whole-cell biocatalysis.
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The incidence of melioidosis cases caused by the gram-negative pathogen Burkholderia pseudomallei (BP) is seeing an increasing trend that has spread beyond its previously known endemic regions. Biofilms produced by BP have been associated with antimicrobial therapy limitation and relapse melioidosis, thus making it urgently necessary to understand the mechanisms of biofilm formation and their role in BP biology. Microbial cells aggregate and enclose within a self-produced matrix of extracellular polymeric substances (EPSs) to form biofilm. The transition mechanism of bacterial cells from planktonic state to initiate biofilm formation, which involves the formation of surface attachment microcolonies and the maturation of the biofilm matrix, is a dynamic and complex process. Despite the emerging findings on the biofilm formation process, systemic knowledge on the molecular mechanisms of biofilm formation in BP remains fractured. This review provides insights into the signaling systems, matrix composition, and the biosynthesis regulation of EPSs (exopolysaccharide, eDNA and proteins) that facilitate the formation of biofilms in order to present an overview of our current knowledge and the questions that remain regarding BP biofilms.
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Antiinfecciosos , Burkholderia pseudomallei , Melioidosis , Humanos , Burkholderia pseudomallei/genética , Melioidosis/microbiología , Biopelículas , Proteínas Bacterianas/genética , Proteínas Bacterianas/metabolismoRESUMEN
In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.
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Sulfur is an essential element required for plant growth and development, physiological processes and stress responses. Sulfur-encoding biosynthetic genes are involved in the primary sulfur assimilation pathway, regulating various mechanisms at the gene, cellular and system levels, and in the biosynthesis of sulfur-containing compounds (SCCs). In this study, the SCC-encoding biosynthetic genes in rice were identified using a sulfur-dependent model plant, the Arabidopsis. A total of 139 AtSCC from Arabidopsis were used as reference sequences in search of putative rice SCCs. At similarity index > 30%, the similarity search against Arabidopsis SCC query sequences identified 665 putative OsSCC genes in rice. The gene synteny analysis showed a total of 477 syntenic gene pairs comprised of 89 AtSCC and 265 OsSCC biosynthetic genes in Arabidopsis and rice, respectively. Phylogenetic tree of the collated (AtSCCs and OsSCCs) SCC-encoding biosynthetic genes were divided into 11 different clades of various sizes comprised of branches of subclades. In clade 1, nearing equal representation of OsSCC and AtSCC biosynthetic genes imply the most ancestral lineage. A total of 25 candidate Arabidopsis SCC homologs were identified in rice. The gene ontology enrichment analysis showed that the rice-Arabidopsis SCC homologs were significantly enriched in the following terms at false discovery rate (FDR) < 0.05: (i) biological process; sulfur compound metabolic process and organic acid metabolic processes, (ii) molecular function; oxidoreductase activity, acting on paired donors with incorporation or reduction of molecular oxygen and (iii) KEGG pathway; metabolic pathways and biosynthesis of secondary metabolites. At less than five duplicated blocks of separation, no tandem duplications were observed among the SCC biosynthetic genes distributed in rice chromosomes. The comprehensive rice SCC gene description entailing syntenic events with Arabidopsis, motif distribution and chromosomal mapping of the present findings offer a foundation for rice SCC gene functional studies and advanced strategic rice breeding.
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Arabidopsis , Oryza , Arabidopsis/genética , Regulación de la Expresión Génica de las Plantas , Genes de Plantas , Genoma de Planta/genética , Familia de Multigenes , Oryza/genética , Filogenia , Fitomejoramiento , Proteínas de Plantas/genética , Plantas/genética , AzufreRESUMEN
Colorectal cancer (CRC) ranks second among the most commonly occurring cancers in Malaysia, and unfortunately, its pathobiology remains unknown. CRC pathobiology can be understood in detail with the implementation of omics technology that is able to generate vast amounts of molecular data. The generation of omics data has introduced a new challenge for data organization. Therefore, a knowledge-based repository, namely TCGA-My, was developed to systematically store and organize CRC omics data for Malaysian patients. TCGA-My stores the genome and metabolome of Malaysian CRC patients. The genome and metabolome datasets were organized using a Python module, pandas. The variants and metabolites were first annotated with their biological information using gene ontologies (GOs) vocabulary. The TCGA-My relational database was then built using HeidiSQL PorTable 9.4.0.512, and Laravel was used to design the web interface. Currently, TCGA-My stores 1,517,841 variants, 23,695 genes, and 167,451 metabolites from the samples of 50 CRC patients. Data entries can be accessed via search and browse menus. TCGA-My aims to offer effective and systematic omics data management, allowing it to become the main resource for Malaysian CRC research, particularly in the context of biomarker identification for precision medicine.
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While chemical fertilisers and pesticides indeed enhance agricultural productivity, their excessive usage has been detrimental to environmental health. In addressing this matter, the use of environmental microbiomes has been greatly favoured as a 'greener' alternative to these inorganic chemicals' application. Challenged by a significant proportion of unidentified microbiomes with unknown ecological functions, advanced high throughput metatranscriptomics is prudent to overcome the technological limitations in unfolding the previously undiscovered functional profiles of the beneficial microbiomes. Under this context, this review begins by summarising (1) the evolution of next-generation sequencing and metatranscriptomics in leveraging the microbiome transcriptome profiles through whole gene expression profiling. Next, the current environmental metatranscriptomics studies are reviewed, with the discussion centred on (2) the emerging application of the beneficial microbiomes in developing fertile soils and (3) the development of disease-suppressive soils as greener alternatives against biotic stress. As sustainable agriculture focuses not only on crop productivity but also long-term environmental sustainability, the second half of the review highlights the metatranscriptomics' contribution in (4) revolutionising the pollution monitoring systems via specific bioindicators. Overall, growing knowledge on the complex microbiome functional profiles is imperative to unlock the unlimited potential of agricultural microbiome-based practices, which we believe hold the key to productive agriculture and sustainable environment.
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Agricultura , Microbiota , Producción de Cultivos , Fertilizantes , Microbiota/genética , SueloRESUMEN
The toxin-producing dinoflagellate Alexandrium minutum is responsible for the outbreaks of harmful algae bloom (HABs). It is a widely distributed species and is responsible for producing paralytic shellfish poisoning toxins. However, the information associated with the environmental adaptation pathway and toxin biosynthesis in this species is still lacking. Therefore, this study focuses on the functional characterization of A. minutum unigenes obtained from transcriptome sequencing using the Illumina Hiseq 4000 sequencing platform. A total of 58,802 (47.05%) unigenes were successfully annotated using public databases such as NCBI-Nr, UniprotKB, EggNOG, KEGG, InterPRO and Gene Ontology (GO). This study has successfully identified key features that enable A. minutum to adapt to the marine environment, including several carbon metabolic pathways, assimilation of various sources of nitrogen and phosphorus. A. minutum was found to encode homologues for several proteins involved in saxitoxin biosynthesis, including the first three proteins in the pathway of saxitoxin biosynthesis, namely sxtA, sxtG and sxtB. The comprehensive transcriptome analysis presented in this study represents a valuable resource for understanding the dinoflagellates molecular metabolic model regarding nutrient acquisition and biosynthesis of saxitoxin.
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Plants produce a wide range of secondary metabolites that play important roles in plant defense and immunity, their interaction with the environment and symbiotic associations. Sulfur-containing compounds (SCCs) are a group of important secondary metabolites produced in members of the Brassicales order. SCCs constitute various groups of phytochemicals, but not much is known about them. Findings from previous studies on SCCs were scattered in published literatures, hence SuCComBase was developed to store all molecular information related to the biosynthesis of SCCs. Information that includes genes, proteins and compounds that are involved in the SCC biosynthetic pathway was manually identified from databases and published scientific literatures. Sets of co-expression data was analyzed to search for other possible (previously unknown) genes that might be involved in the biosynthesis of SCC. These genes were named as potential SCC-related encoding genes. A total of 147 known and 92 putative Arabidopsis thaliana SCC-related genes from literatures were used to identify other potential SCC-related encoding genes. We identified 778 potential SCC-related encoding genes, 4026 homologs to the SCC-related encoding genes and 116 SCCs as shown on SuCComBase homepage. Data entries are searchable from the Main page, Search, Browse and Datasets tabs. Users can easily download all data stored in SuCComBase. All publications related to SCCs are also indexed in SuCComBase, which is currently the first and only database dedicated to plant SCCs. SuCComBase aims to become a manually curated and au fait knowledge-based repository for plant SCCs.